Entropy Guided Transformation Learning (ETL) is a new machine learning strategy that combines the advantages of decision trees (DT) and Transformation Based Learning (TBL). In this work, we apply the ETL framework to four phrase chunking tasks: Portuguese noun phrase chunking, English base noun phrase chunking, English text chunking and Hindi text chunking. In all four tasks, ETL shows better results than Decision Trees and also than TBL with hand-crafted templates.